Why might you choose an R Data Frame over an R Matrix?

a) When you need to store data of different types in a two-dimensional structure

b) When you need to perform linear algebra operations

c) When you need a multi-dimensional data structure

d) When you need to store data in a single type

Answer:

a) When you need to store data of different types in a two-dimensional structure

Explanation:

You might choose an R data frame over an R matrix when you need to store data of different types in a two-dimensional structure. Data frames allow each column to hold a different type of data (e.g., numeric, character, factor), making them more versatile for handling diverse datasets.

# Creating a data frame with different types of data
my_data_frame <- data.frame(
    Name = c("Alice", "Bob", "Charlie"),
    Age = c(25, 30, 35),
    Salary = c(50000, 60000, 70000)
)

# Creating a matrix with numeric data only
my_matrix <- matrix(1:6, nrow = 2, ncol = 3)

# Printing the data frame
print(my_data_frame)

# Printing the matrix
print(my_matrix)

In this example, the data frame my_data_frame can store a mix of character and numeric data, while the matrix my_matrix is restricted to numeric data only. This makes data frames more suitable for real-world datasets where data types may vary across columns.